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检索条件"任意字段=18th International Workshop on Design and Architecture for Signal and Image Processing, DASIP 2025"

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18th international workshop on design and architecture for signal and image processing, dasip 2025

18th International Workshop on Design and Architecture for S...

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18th international workshop on design and architecture for signal and image processing, dasip 2025

ISBN: (纸本)9783031878961

the proceedings contain 10 papers. the special focus in this conference is on design and architectures for signal and image processing. the topics include: LiFT: Lightweight, FPGA-Tailored 3D Object Detection Based on LiDAR Data;A Practical HW-Aware NAS Flow for AI Vision Applications on Embedded Heterogeneous SoCs;Endoscopy image Classification for Wireless Capsules with CNNs on Microcontroller-Based Platforms;joint Underwater Depth Estimation and Dehazing from a Single image Using Attention U-Net;KD-AHOSVD: Neural Network Compression via Knowledge Distillation and Tensor Decomposition;Novel Scheduling and Shifter Networks for 5G LDPC Decoders;Comparison Between In-Core Hardware IDS, Off-Core Hardware IDS and Software IDS;comparative Study of Memory Optimization Techniques for Dataflow-Modeled Applications.

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Joint Underwater Depth Estimation and Dehazing from a Single image Using Attention U-Net 18th

Joint Underwater Depth Estimation and Dehazing from a Sin...

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18th international workshop on design and architecture for signal and image processing, dasip 2025

作者： Nazir, Saqib Asiyabi, Reza Mohammadi Lezoray, Olivier Normandie Univ UNICAEN ENSICAEN CNRS GREYC Caen France School of GeoSciences The University of Edinburgh Edinburgh United Kingdom

ISBN: (纸本)9783031878961

Underwater imaging presents unique challenges compared to open-air photography, primarily due to diminished visibility and geometric distortions, impeding the development of underwater Computer Vision (CV) and robotic vision perception. Previous methods relying on simplified image formation models for image enhancement have often yielded unsatisfactory results. this paper proposes a new deep learning-based architecture for joint depth estimation and dehazing from a single underwater monocular image, seeking to take advantage of the mutual benefits between these two interrelated tasks. the proposed architecture is a Two-Headed Depth Estimation and Dehazing Attention Network (2HDED:AttN) with an end-to-end training approach. Comprehensive experiments on synthetic and real underwater datasets showcase the proposed architecture’s superior performance in jointly addressing underwater depth estimation and image dehazing tasks. the method effectively estimates underwater depth and improves underwater image quality, paving the way for enhanced underwater computer and robotic vision applications. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Robot vision

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Endoscopy image Classification for Wireless Capsules with CNNs on Microcontroller-Based Platforms 18th

Endoscopy Image Classification for Wireless Capsules with ...

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18th international workshop on design and architecture for signal and image processing, dasip 2025

作者： Busia, Paola Pinna, Andrea Meloni, Paolo DIEE University of Cagliari Cagliari09123 Italy Sorbonne University CNRS LIP6 Paris75005 France

ISBN: (纸本)9783031878961

Wireless Capsule Endoscopy (WCE) offers an important diagnostic instrument for different gastrointestinal diseases. Enhancing the WCE device with real-time image processing capabilities allows to assist specialized physicians in the long and cumbersome process of inspecting the significant amount of data acquired during the examination procedure, providing the first detection of the signs of relevant diseases that require further attention. In this work, we evaluate different state-of-the-art Convolutional Neural Network models for real-time WCE image classification, focusing on lightweight topologies suitable for execution on low-power microcontroller platforms and integration on the WCE device. the selected WCE-SqueezeNet model achieves 98.5% accuracy in the classification of ulcerative colitis, polyps, and esophagitis against healthy samples, allowing classification at a 16 fps rate on the GAP9 multi-core platform, with 61 ms inference time and 30.6 mW average core power consumption. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Endoscopy

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design and architecture for signal and image processing 1

Design and Architecture for Signal and Image Processing

引用

丛书名： Lecture Notes in Computer Science

1000年

作者： Jordane Lorandel Ahmed Kamaleldin

ISBN: (数字)9783031878978

ISBN: (纸本)9783031878961

this book constitutes the refereed conference proceedings of the 18th international workshop on design and architecture for signal and image processing, dasip 2025, held in Barcelona, Spain, during January 20-22, 2025. the 10 full papers included in this book were carefully reviewed and selected from 23 *** were organized in topical sections as follows: Specialized Hardware architecture for Efficient processing; Efficient processing using AI for image, Vision and signal Applications, and Analysis of Emerging Techniques for signal processing Applications.

关键词： signal, image and Speech processing Machine Learning

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A Highly Configurable Platform for Advanced PPG Analysis 17th

A Highly Configurable Platform for Advanced PPG Analysis

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17th international workshop on design and architecture for signal and image processing (dasip)

作者： De Gevigney, Flavie Durand Heulot, Julien Bazin, Eric Nezan, Jean-Francois Dardaillon, Mickael Aridhi, Slaheddine Univ Rennes INSA Rennes CNRS IETR UMR6164 Rennes France Sensoria Analyt Valbonne France

ISBN: (纸本)9783031628733;9783031628740

Growing interest in healthcare applications has made biomedical engineering one of the fastest growing disciplines in recent years. Photoplethysmography (PPG) is one of these trends since PPG sensors are embedded into many devices like smartwatches or oximeters. Due to the versatility of PPG, it is the technique of choice for the non-invasive monitoring of vital signs such as heart rate, respiratory rate, blood oxygen saturation and blood pressure. However, commercial pulse oximeters often use proprietary data acquisition and visualization techniques, making digital signal processing on raw data difficult or impossible. this paper presents a hardware platform for the exploration of new biological signal analysis based on PPG. the originality of the platform is to expand the number of wavelengths to 8 and to allow the parameterization of the acquisition by choosing the sample rate. this allows the PPG sensor to be adapted to the needs of analysis on the whole signal or perform high precision measurements. Much consideration has been given to the accurate data acquisition during sports activities.

关键词： Photoplethysmography PPG Multi-wavelength Mixed signal Heart Rate SpO2

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